Principal component analyses

Methods:

Principal component analysis (PCA) (function prcomp) of scaled and centered physiological parameters (host carbohydrate, host lipid, host protein, algal endosymbiont chlorophyll a, algal endosymbiont cell density, holobiont calcification rate as previously for the same samples in Bove et al. (2019)) were employed to assess the relationship between physiological parameters and treatment conditions for each coral species. Main effects (temperature, pCO2, and reef environment) were evaluated with PERMANOVA using the adonis2 function (vegan package; version 2.5.7) (Tables XXX).


Results:

Two principal components (PCs) explained approximately 66% of the variance in physiological responses of the S. siderea holobiont to ocean acidification and warming treatments (Figure 1A). PC1 was driven by differences in algal endosymbiont physiology (chlorophyll a, cell density), while PC2 represented an inverse relationship between host energy reserves (lipid, protein, carbohydrate) and calcification rates and colour intensities. Overall, lower pCO2 and temperature resulted in higher S. siderea holobiont physiology (Figure 1A). Treatment pCO2 predominantly drove S. siderea physiological responses (p < 0.001; Table S2), while temperature and reef environment were not as strong of drivers in pysiological responses (p > 0.01 and p > 0.01, respectively; Table S2). For P. strigosa, 74% of the variance in the holobiont responses to treatments was explained by two PCs (Figure 1B). PC1 explained most of the variation of physiological parameters with the exception of host lipid content, which was represented in PC2. Holobiont physiology of P. strigosa was clearly reduced under warming and was generally higher in the lower pCO2 treatments (Figure 1B). Treatment temperature (p < 0.001; Table S2), pCO2 (p < 0.01; Table S2), and natal reef environment all significantly drove coral holobiont physiology (p < 0.001; Table S2). Finally, the first two PCs explained about 59% of the total variance of the P. astreoides holobiont response to treatment (Figure 1C). Coral holobiont samples separated most clearly along PC1 driven primarily by calcification rate and algal endosymbiont density, while PC2 exhibited an inverse relationship between host total carbohydrate and colour intensity. Overall, lower pCO2 drove higher P. astreoides holobiont physiology, while elevated temperature resulted in greater holobiont physiology (Figure 1C). Temperature (p < 0.001; Table S2) and pCO2 (p < 0.001; Table S2) drove separations in P. astreoides holobiont physiology, while reef environment was nonsignificant (p = 0.82; Table S2).


Siderastrea siderea

## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 1500
## 
## adonis2(formula = sid_pca_df ~ fpco2 + ftemp + reef, data = s_df, permutations = bootnum, method = "eu")
##          Df SumOfSqs      R2       F    Pr(>F)    
## fpco2     3   150243 0.27232 11.4516 0.0006662 ***
## ftemp     1    24935 0.04520  5.7018 0.0053298 ** 
## reef      1    26681 0.04836  6.1009 0.0033311 ** 
## Residual 80   349861 0.63413                      
## Total    85   551720 1.00000                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1



Pseudodiploria strigosa

## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 1500
## 
## adonis2(formula = dip_pca_df ~ reef + fpco2 + ftemp, data = p_df, permutations = bootnum, method = "eu")
##          Df SumOfSqs      R2       F    Pr(>F)    
## reef      1   162037 0.07959 10.9355 0.0006662 ***
## fpco2     3   196323 0.09644  4.4165 0.0019987 ** 
## ftemp     1   625389 0.30720 42.2061 0.0006662 ***
## Residual 71  1052041 0.51677                      
## Total    76  2035789 1.00000                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1



Porites astreoides

## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 1500
## 
## adonis2(formula = por_pca_df ~ reef + ftemp + fpco2, data = a_df, permutations = bootnum, method = "eu")
##          Df SumOfSqs      R2       F    Pr(>F)    
## reef      1      505 0.00150  0.1692 0.8194537    
## ftemp     1    56228 0.16639 18.8252 0.0006662 ***
## fpco2     3    96015 0.28412 10.7153 0.0006662 ***
## Residual 62   185186 0.54799                      
## Total    67   337935 1.00000                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1



Figure 1

Figure 1. Principal component analysis (PCA) of all coral holobiont physiological parameters for S. siderea (A), P. strigosa (B), and P. astreoides (C) after 93 days of exposure to different temperature and pCO2 treatments. PCAs in the top row are depicted by temperature treatment for each species (28\(^\circ\) C blue; 31\(^\circ\) C red) and the bottom row of PCAs are depicted by pCO2 for each species (280 \(\mu\)atm light purple; 400 \(\mu\)atm dark purple; 700 \(\mu\)atm light orange; 2800 \(\mu\)atm dark orange). Arrows represent significant (p < 0.05) correlation vectors for physiological parameters and ellipses represent 95% confidence based on multivariate t-distributions.



Correlation assessments

Methods:

Correlations of all physiological parameters were assessed to determine the relationships between parameters within each species. The Pearson correlation coefficient (R2) of each comparison was calculated using the corrgram package (version 1.13) and the significance was calculated using the cor.test function. These relationships were then visualized through simple scatterplots.


Results:

Text for results of correlations will go here


Figure 2. Coral holobiont correlation matrices (bottom panel) and scatter plots (top panel) for S. siderea (A), P. strigosa (B), and P. astreoides (C) depicting pairwise comparisons of physiological parameters within each species. Strength of correlations between parameters is indicated by darker shades of blue in the bottom panel with a higher R2 value (Pearson correlation coefficient). Of these correlations, significant correlations are depicted with asterisks according to significance level (* p < 0.05; ** p < 0.01; *** p < 0.001). Scatter plots of physiological parameters are displayed in the top panel with temperature depicted by shape (28\(^\circ\)C filled points; 31\(^\circ\)C open points) and pCO2 depicted by colour (280 \(\mu\)atm light purple; 400 \(\mu\)atm dark purple; 700 \(\mu\)atm light orange; 2800 \(\mu\)atm dark orange).



Plasticity analyses

Methods:

Using PC1 and PC2 for each species, we then calculated the phenotypic plasticity of each experimental fragment. Plasticity was calculated as the PC distance between an experimental fragment and the control (400 \(\mu\)atm; 28\(^\circ\)C) fragment from that same colony. The effects of treatment (pCO2 and temperature) and natal reef environment on calculated distances were assessed using generalized linear models (function glm) with a Gamma distribution and log-link. The best-fit model was selected as the model with the lowest AIC for each species (Table SXX). All figures and statistical analyses were carried out in R version 3.6.3 (R Core Development Team 2016).


Results:

Text for results of correlations will go here


Siderastrea siderea

## 
## Call:
## glm(formula = dist ~ reef * fpco2 + ftemp, family = Gamma(link = "log"), 
##     data = sid_dist)
## 
## Deviance Residuals: 
##     Min       1Q   Median       3Q      Max  
## -1.5392  -0.4066  -0.1219   0.2076   1.6019  
## 
## Coefficients:
##                 Estimate Std. Error t value Pr(>|t|)   
## (Intercept)      0.51132    0.23350   2.190  0.03208 * 
## reefN            0.19484    0.33128   0.588  0.55845   
## fpco2420         0.52611    0.39569   1.330  0.18823   
## fpco2680         0.33298    0.29535   1.127  0.26366   
## fpco23300        0.81399    0.30087   2.705  0.00867 **
## ftemp31          0.05814    0.17126   0.339  0.73532   
## reefN:fpco2420  -1.08912    0.52812  -2.062  0.04312 * 
## reefN:fpco2680  -0.68937    0.43708  -1.577  0.11953   
## reefN:fpco23300 -0.63546    0.43202  -1.471  0.14607   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## (Dispersion parameter for Gamma family taken to be 0.4613617)
## 
##     Null deviance: 36.807  on 74  degrees of freedom
## Residual deviance: 27.862  on 66  degrees of freedom
## AIC: 254.68
## 
## Number of Fisher Scoring iterations: 6

Pseudodiploria strigosa

## 
## Call:
## glm(formula = dist ~ reef + fpco2 * ftemp, family = Gamma(link = "log"), 
##     data = dip_dist)
## 
## Deviance Residuals: 
##     Min       1Q   Median       3Q      Max  
## -1.5003  -0.4829  -0.1345   0.2421   1.5593  
## 
## Coefficients: (1 not defined because of singularities)
##                   Estimate Std. Error t value Pr(>|t|)    
## (Intercept)        0.98763    0.16396   6.024 9.23e-08 ***
## reefN              0.06115    0.14842   0.412   0.6817    
## fpco2420           0.24640    0.34415   0.716   0.4766    
## fpco2680          -0.28048    0.22590  -1.242   0.2189    
## fpco23300         -0.45279    0.22174  -2.042   0.0453 *  
## ftemp31           -0.31996    0.25724  -1.244   0.2181    
## fpco2420:ftemp31        NA         NA      NA       NA    
## fpco2680:ftemp31   0.22609    0.41179   0.549   0.5849    
## fpco23300:ftemp31  0.86790    0.37310   2.326   0.0232 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## (Dispersion parameter for Gamma family taken to be 0.3805534)
## 
##     Null deviance: 27.294  on 71  degrees of freedom
## Residual deviance: 24.400  on 64  degrees of freedom
## AIC: 239.68
## 
## Number of Fisher Scoring iterations: 6

Porites astreoides

## 
## Call:
## glm(formula = dist ~ fpco2 + ftemp, family = Gamma(link = "log"), 
##     data = por_dist)
## 
## Deviance Residuals: 
##      Min        1Q    Median        3Q       Max  
## -1.38209  -0.40297  -0.05695   0.25701   1.10124  
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   0.6688     0.1363   4.908  9.5e-06 ***
## fpco2420     -0.1677     0.2642  -0.635   0.5283    
## fpco2680      0.1270     0.1750   0.726   0.4710    
## fpco23300     0.2039     0.1803   1.131   0.2634    
## ftemp31       0.2976     0.1532   1.942   0.0575 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## (Dispersion parameter for Gamma family taken to be 0.265958)
## 
##     Null deviance: 16.944  on 56  degrees of freedom
## Residual deviance: 15.571  on 52  degrees of freedom
## AIC: 186.42
## 
## Number of Fisher Scoring iterations: 5

Figure 3

Figure 3. Assessment of phenotypic plasticity of S. siderea (A), P. strigosa (B), and P. astreoides (C) in experimental treatments and by natal reef environment. Higher values represent greater plasticity in coral holobiont samples. pCO2 treatment is depicted by colour and shape (280 \(\mu\)atm light purple, circle; 400 \(\mu\)atm dark purple, diamond; 700 \(\mu\)atm light orange, triangle; 2800 \(\mu\)atm dark orange, square) and temperature is represented as either filled (28\(^\circ\)C) or open (31\(^\circ\)C) symbols.



Physiological paramters

Physiological response parameters were assessed using mixed-effects linear models across species and treatments. Model selection was carried out using backward elimination of random-effects followed by fixed-effects using the package lmerTest (version 3.1.3)

Protein

While value ~ species + fpco2 + ftemp + (1 | colony) + species:ftemp was the best-fit model structure identified, we wanted to model both pCO2 and temperature responses by species so moving forward we are using the following model structure:

value ~ species * (fpco2 + ftemp) + (1 | colony)


Figure:

Carbohydrate

While value ~ species + ftemp was the best-fit model structure identified, we wanted to model responses with a random effect of colony so moving forward we are using the following model structure:

value ~ species * (fpco2 + ftemp) + (1 | colony)


Figure:

Lipid

While value ~ species + ftemp + reef + species:ftemp + species:reef was the best-fit model structure identified, we wanted to model both pCO2 and temperature responses by species and with random effect of colony so moving forward we are using the following model structure:

value ~ species * (fpco2 + ftemp) + reef + species:reef + (1 | colony)


Figure:

Density

While value ~ species + fpco2 + ftemp + reef + (1 | colony) + species:fpco2 + species:ftemp + fpco2:ftemp + species:reef + fpco2:reef + ftemp:reef + species:fpco2:ftemp + species:fpco2:reef + species:ftemp:reef + fpco2:ftemp:reef + species:fpco2:ftemp:reef was the best-fit model structure identified, we wanted to model both pCO2 and temperature responses by species and with random effect of colony so moving forward we are using the following model structure:

value ~ species * (fpco2 + ftemp) + reef + species:reef + (1 | colony)


Figure:

Chlorophyll

Since the best-fit model fits our design, we will proceed with the following model structure:

value ~ species + fpco2 + ftemp + reef + (1 | colony) + species:fpco2 + species:ftemp + fpco2:ftemp + species:reef


Figure:

Total Host

Since the best-fit model fits our design, we will proceed with the following model structure:

value ~ species + fpco2 + ftemp + reef + (1 | colony) + species:fpco2 + species:ftemp + species:reef + fpco2:reef + species:fpco2:reef


Figure:

Calcification

This is the same model from Bove et al 2019, just matching aesthetics for this manuscript.

Figure S1


Figure S1. Modeled 95% confidence interval of (A) host total protein (mg cm-2), (B) host total carbohydrate (mg cm-2), (C) host total lipid (mg cm-2), (D) cell density (106 cells cm-2), and (E) Chlorophyll a (ug cm-2) for S. siderea (left), P. strigosa (center), and P. astreoides (right) at T0 (green) or T90 (red/blue), with individual coral fragment physiology denoted by points. Blue denotes 28°C and red denotes 31°C, with pCO2 treatment along the x axis.



S. siderea gene expression subset

SSID subset PCA

## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 1500
## 
## adonis2(formula = s_df_sub[, c(14:17, 21:23, 29)] ~ fpco2 + fpco2:domSymb + domSymb + ftemp, data = s_df_sub, permutations = bootnum, method = "eu")
##               Df SumOfSqs      R2       F    Pr(>F)    
## fpco2          3    60040 0.26137 12.2655 0.0006662 ***
## domSymb        2    76699 0.33389 23.5033 0.0006662 ***
## ftemp          1    13933 0.06065  8.5391 0.0013324 ** 
## fpco2:domSymb  6    28458 0.12389  2.9068 0.0039973 ** 
## Residual      31    50582 0.22020                      
## Total         43   229711 1.00000                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1



Siderastrea siderea subset



Supplemental Tables

Table 1. T90 modeled mean coral host protein content and 95% confidence intervals for each species
treatment N mean lower 95% upper 95%
(a) SSID
300_28 11 0.54 0.47 0.60
300_31 9 0.48 0.41 0.55
3300_28 12 0.43 0.37 0.50
3300_31 12 0.38 0.31 0.44
420_28 12 0.50 0.43 0.57
420_31 12 0.45 0.38 0.51
680_28 13 0.46 0.39 0.53
680_31 12 0.40 0.34 0.47
(b) PSTR
300_28 16 0.53 0.47 0.59
300_31 9 0.27 0.19 0.35
3300_28 16 0.43 0.36 0.49
3300_31 8 0.17 0.09 0.24
420_28 5 0.49 0.42 0.56
420_31 6 0.23 0.15 0.32
680_28 14 0.45 0.39 0.51
680_31 5 0.19 0.11 0.28
(c) PAST
300_28 11 0.23 0.17 0.30
300_31 6 0.19 0.10 0.27
3300_28 12 0.13 0.06 0.20
3300_31 4 0.08 0.00 0.17
420_28 12 0.20 0.13 0.26
420_31 7 0.15 0.07 0.23
680_28 10 0.16 0.09 0.22
680_31 9 0.11 0.03 0.19
Table 1. T90 modeled mean coral host lipid content and 95% confidence intervals for each species
treatment N mean lower 95% upper 95%
(a) SSID
300_28 11 0.37 0.30 0.44
300_31 9 0.35 0.28 0.42
3300_28 12 0.37 0.30 0.44
3300_31 12 0.35 0.28 0.42
420_28 12 0.37 0.30 0.44
420_31 12 0.35 0.27 0.42
680_28 13 0.38 0.31 0.45
680_31 12 0.36 0.29 0.43
(b) PSTR
300_28 16 0.24 0.17 0.31
300_31 9 0.11 0.02 0.20
3300_28 15 0.24 0.17 0.31
3300_31 8 0.10 0.02 0.19
420_28 5 0.24 0.17 0.31
420_31 5 0.11 0.02 0.20
680_28 14 0.24 0.17 0.31
680_31 5 0.11 0.02 0.20
(c) PAST
300_28 11 0.15 0.08 0.23
300_31 6 0.20 0.11 0.29
3300_28 12 0.16 0.08 0.23
3300_31 4 0.22 0.14 0.31
420_28 12 0.16 0.08 0.23
420_31 7 0.20 0.11 0.29
680_28 10 0.16 0.08 0.23
680_31 9 0.20 0.11 0.29
Table 1. T90 modeled mean coral host carbohydrate content and 95% confidence intervals for each species
treatment N mean lower 95% upper 95%
(a) SSID
300_28 11 1.15 0.95 1.35
300_31 8 0.82 0.61 1.02
3300_28 12 1.10 0.91 1.29
3300_31 12 0.77 0.60 0.96
420_28 12 1.08 0.90 1.26
420_31 12 0.75 0.57 0.94
680_28 13 1.27 1.10 1.45
680_31 12 0.94 0.75 1.11
(b) PSTR
300_28 16 0.77 0.60 0.93
300_31 9 0.50 0.30 0.68
3300_28 16 0.62 0.45 0.78
3300_31 8 0.34 0.15 0.55
420_28 5 0.67 0.41 0.92
420_31 6 0.40 0.16 0.65
680_28 14 0.56 0.37 0.75
680_31 7 0.29 0.07 0.51
(c) PAST
300_28 11 0.82 0.61 1.03
300_31 6 0.65 0.41 0.88
3300_28 12 0.58 0.38 0.78
3300_31 4 0.41 0.16 0.65
420_28 12 0.90 0.71 1.10
420_31 7 0.73 0.51 0.95
680_28 10 0.61 0.41 0.81
680_31 9 0.43 0.23 0.64
Table 1. T90 modeled mean coral symbiont density content and 95% confidence intervals for each species
treatment N mean lower 95% upper 95%
(a) SSID
300_28 11 3.32 2.23 4.46
300_31 9 2.45 1.33 3.58
3300_28 12 2.04 0.97 3.07
3300_31 12 1.18 0.12 2.23
420_28 12 3.48 2.42 4.50
420_31 12 2.61 1.55 3.67
680_28 13 2.96 1.95 3.98
680_31 12 2.10 1.04 3.14
(b) PSTR
300_28 16 2.16 1.14 3.15
300_31 9 0.42 -0.77 1.60
3300_28 16 1.53 0.53 2.52
3300_31 8 -0.27 -1.48 0.89
420_28 5 2.16 0.75 3.61
420_31 6 0.45 -0.96 1.86
680_28 14 1.71 0.68 2.75
680_31 7 -0.09 -1.30 1.14
(c) PAST
300_28 11 7.29 6.13 8.48
300_31 6 6.42 5.02 7.74
3300_28 12 5.92 4.74 7.16
3300_31 4 4.86 3.51 6.15
420_28 12 6.43 5.28 7.57
420_31 6 5.51 4.22 6.83
680_28 10 5.09 3.84 6.35
680_31 8 4.19 2.87 5.45
Table 1. T90 modeled mean coral symbiont chlorophyll a content and 95% confidence intervals for each species
treatment N mean lower 95% upper 95%
(a) SSID
300_28 11 112.38 81.74 143.62
300_31 9 105.47 71.18 140.02
3300_28 12 48.52 17.15 79.21
3300_31 12 32.61 3.07 63.16
420_28 12 155.21 122.77 186.81
420_31 12 77.84 46.62 108.58
680_28 13 83.24 53.49 114.40
680_31 12 82.41 51.78 113.66
(b) PSTR
300_28 16 185.93 157.24 214.55
300_31 9 120.37 85.65 154.64
3300_28 16 78.53 51.36 106.93
3300_31 8 -1.42 -37.11 34.23
420_28 5 161.17 118.71 202.49
420_31 6 26.74 -14.58 66.79
680_28 14 84.10 54.62 114.41
680_31 5 17.96 -22.30 58.03
(c) PAST
300_28 11 97.02 63.84 130.54
300_31 6 155.01 116.85 192.29
3300_28 12 15.56 -18.42 45.96
3300_31 4 61.04 19.29 101.45
420_28 12 64.66 33.23 97.25
420_31 7 51.82 15.19 89.83
680_28 10 33.69 1.31 67.61
680_31 9 96.83 62.24 133.28
Table 1. T90 modeled mean coral host energy reserves and 95% confidence intervals for each species
treatment N mean lower 95% upper 95%
(a) SSID
300_28 11 2.02 1.61 2.43
300_31 8 1.62 1.21 2.04
3300_28 12 1.92 1.56 2.28
3300_31 12 1.53 1.17 1.89
420_28 12 2.02 1.65 2.40
420_31 12 1.58 1.21 1.95
680_28 13 2.06 1.70 2.41
680_31 12 1.65 1.29 2.01
(b) PSTR
300_28 16 1.60 1.25 1.94
300_31 9 0.96 0.58 1.35
3300_28 15 1.28 0.92 1.64
3300_31 8 0.60 0.20 0.99
420_28 5 1.39 0.84 1.94
420_31 5 0.71 0.14 1.27
680_28 14 1.23 0.82 1.62
680_31 5 0.56 0.11 1.00
(c) PAST
300_28 11 1.26 0.84 1.69
300_31 6 1.12 0.65 1.60
3300_28 12 0.86 0.41 1.29
3300_31 4 0.56 0.13 0.98
420_28 12 1.26 0.86 1.66
420_31 7 1.14 0.71 1.58
680_28 10 0.85 0.44 1.25
680_31 9 0.72 0.31 1.14


Session information

Session information from the last run date on 2021-04-26:

## R version 3.6.3 (2020-02-29)
## Platform: x86_64-apple-darwin15.6.0 (64-bit)
## Running under: macOS High Sierra 10.13.6
## 
## Matrix products: default
## BLAS:   /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRlapack.dylib
## 
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
## 
## attached base packages:
## [1] grid      stats     graphics  grDevices utils     datasets  methods  
## [8] base     
## 
## other attached packages:
##  [1] png_0.1-7          MASS_7.3-53.1      performance_0.7.1  wesanderson_0.3.6 
##  [5] RColorBrewer_1.1-2 gridGraphics_0.5-1 corrplot_0.84      Hmisc_4.5-0       
##  [9] Formula_1.2-4      survival_3.2-10    magick_2.7.1       ggpubr_0.4.0      
## [13] vroom_1.4.0        lmerTest_3.1-3     lme4_1.1-26        Matrix_1.3-2      
## [17] kableExtra_1.3.4   finalfit_1.0.2     ggfortify_0.4.11   cowplot_1.1.1     
## [21] Rmisc_1.5          shiny_1.6.0        vegan_2.5-7        lattice_0.20-41   
## [25] permute_0.9-5      forcats_0.5.1      stringr_1.4.0      purrr_0.3.4       
## [29] tibble_3.1.0       tidyverse_1.3.0    plotly_4.9.3       openxlsx_4.2.3    
## [33] corrgram_1.13      tidyr_1.1.3        ggbiplot_0.55      scales_1.1.1      
## [37] plyr_1.8.6         dplyr_1.0.5        ggplot2_3.3.3      readr_1.4.0       
## [41] knitr_1.31        
## 
## loaded via a namespace (and not attached):
##   [1] readxl_1.3.1        backports_1.2.1     systemfonts_1.0.1  
##   [4] lazyeval_0.2.2      splines_3.6.3       digest_0.6.27      
##   [7] foreach_1.5.1       htmltools_0.5.1.1   fansi_0.4.2        
##  [10] checkmate_2.0.0     magrittr_2.0.1      cluster_2.1.1      
##  [13] see_0.6.3           modelr_0.1.8        svglite_2.0.0      
##  [16] jpeg_0.1-8.1        colorspace_2.0-0    ggrepel_0.9.1      
##  [19] rvest_1.0.0         haven_2.3.1         xfun_0.22          
##  [22] crayon_1.4.1        jsonlite_1.7.2      iterators_1.0.13   
##  [25] glue_1.4.2          registry_0.5-1      gtable_0.3.0       
##  [28] emmeans_1.5.5-1     webshot_0.5.2       car_3.0-10         
##  [31] abind_1.4-5         mvtnorm_1.1-1       DBI_1.1.1          
##  [34] rstatix_0.7.0       Rcpp_1.0.6          htmlTable_2.1.0    
##  [37] viridisLite_0.3.0   xtable_1.8-4        foreign_0.8-75     
##  [40] bit_4.0.4           htmlwidgets_1.5.3   httr_1.4.2         
##  [43] ellipsis_0.3.1      mice_3.13.0         farver_2.1.0       
##  [46] pkgconfig_2.0.3     nnet_7.3-15         sass_0.3.1         
##  [49] dbplyr_2.1.1        utf8_1.2.1          effectsize_0.4.4-1 
##  [52] labeling_0.4.2      tidyselect_1.1.0    rlang_0.4.10       
##  [55] later_1.1.0.1       munsell_0.5.0       cellranger_1.1.0   
##  [58] tools_3.6.3         cli_2.4.0           generics_0.1.0     
##  [61] ggridges_0.5.3      broom_0.7.6         evaluate_0.14      
##  [64] fastmap_1.1.0       yaml_2.2.1          bit64_4.0.5        
##  [67] fs_1.5.0            zip_2.1.1           nlme_3.1-152       
##  [70] mime_0.10           xml2_1.3.2          compiler_3.6.3     
##  [73] rstudioapi_0.13     curl_4.3            ggsignif_0.6.1     
##  [76] reprex_2.0.0        statmod_1.4.35      bslib_0.2.4        
##  [79] stringi_1.5.3       parameters_0.13.0   highr_0.8          
##  [82] nloptr_1.2.2.2      vctrs_0.3.7         pillar_1.6.0       
##  [85] lifecycle_1.0.0     jquerylib_0.1.3     estimability_1.3   
##  [88] insight_0.13.2      data.table_1.14.0   seriation_1.2-9    
##  [91] httpuv_1.5.5        R6_2.5.0            latticeExtra_0.6-29
##  [94] promises_1.2.0.1    TSP_1.1-10          gridExtra_2.3      
##  [97] rio_0.5.26          codetools_0.2-18    boot_1.3-27        
## [100] assertthat_0.2.1    withr_2.4.1         bayestestR_0.9.0   
## [103] mgcv_1.8-34         parallel_3.6.3      hms_1.0.0          
## [106] rpart_4.1-15        coda_0.19-4         minqa_1.2.4        
## [109] rmarkdown_2.7       carData_3.0-4       numDeriv_2016.8-1.1
## [112] lubridate_1.7.10    base64enc_0.1-3